Web-based customer service interface

ABSTRACT

A system and method for processing a web-based query is provided. The system comprises a web server for transmitting a web form having a text field box for entering a natural language query, and a language analysis server for extracting concepts from the natural language query and classifying the natural language query into predefined categories via computed match scores based upon the extracted concepts and information contained within an adaptable knowledge base. In various embodiments, the web server selectively transmits either a resource page or a confirmation page to the client, based upon the match scores. The resource page may comprise at least one suggested response corresponding to at least one predefined category. The language analysis server may adapt the knowledge base in accordance with a communicative action received from the client after the resource page is transmitted.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority and benefit of U.S. ProvisionalPatent Application Ser. No. 60/468,576 entitled “Web-Based CustomerService Interface,” filed on May 6, 2003, which is hereby incorporatedby reference. This application is related to patent application Ser. No.______, entitled, “System and Method for Electronic CommunicationManagement,” herein incorporated by reference, filed on an even dateherewith.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to electronic communications andrelates more particularly to a system and method for a web-basedcustomer service interface.

2. Description of the Background Art

In a typical organization, communications with customers and others mayoccur via a variety of different channels. In addition to traditionalchannels such as letters and telephone calls, customers may alsocommunicate with an organization via electronic mail, facsimile,web-based forms, web-based chat, and wireless communication and voice.An organization will most likely incorporate these and any other newlydeveloped communication channels to allow customers to communicate in away they find most convenient.

Many of the communication channels mentioned above contain informationthat is unstructured in nature, usually expressed in natural language.Different customers may make identical requests each in a unique way,using different communication channels, different words and expressions,or both. Human agents are usually required to review each naturallanguage communication to evaluate the customer's intent, and todetermine what information or action would be responsive to that intent.

Agents typically must look to various sources to gather all of theinformation required to respond appropriately to a customercommunication. The information may be retrieved from a variety ofsources, such as legacy systems, databases, back office systems, andfront office systems. Each of these sources may store data in a uniquestructure or format. An agent typically gathers and organizes therequired information from one or more of these information sources anduses the information to compose an appropriate content-rich reply thatis responsive to the customer's intent.

Utilizing people to respond to customer communications is ofteninefficient. In addition, an increase in the number of communicationsreceived by an organization typically requires an even larger increasein the number of people required to provide an acceptable level ofcustomer service.

Several types of automatic systems exist for responding to customercommunications. Rule-based systems, keyword-based systems, andstatistical systems typically do not perform with the necessary accuracyto substantially automate business processes, such as responding tocustomer inquiries, and require a large investment in resources to keepthem up-to-date. Many learning systems utilize a training set of datathat is a poor representation of the system's world, which reduces theaccuracy of the system and makes the process of updating the system verycumbersome.

SUMMARY OF THE INVENTION

The present invention provides a system and method for processing aweb-based query. In one embodiment of the invention, the systemcomprises a web server for transmitting a web form having at least onetext field box for entering a natural language query to a client, and alanguage analysis server for analyzing the natural language query andoptional meta-data received from the client to classify the naturallanguage query into at least one predefined category based oninformation contained within a knowledge base. The web server is furtherconfigured to selectively transmit a resource page to the client, wherethe resource page includes at least one suggested response andoptionally other data corresponding to at least one predefined category.In addition, the web server is further configured to receive acommunicative action from the client after the resource page istransmitted, wherein the language analysis server may adapt theknowledge base in accordance with the communicative action.

In one embodiment of the invention, the language analysis serverclassifies the natural language query into predefined categories basedon computed match scores, where each match score corresponds to one ofthe predefined categories. Furthermore, each match score isrepresentative of a confidence level that the natural language query isrelevant to a corresponding predefined category. The language analysisserver calculates each match score based upon a comparison of conceptsextracted from the natural language query to concepts associated withthe predefined categories. Each match score is representative of astatistical likelihood of the natural language query being correctlyclassified to the corresponding predefined category

In another embodiment of the invention, the language analysis serverroutes the natural language query to an agent based upon an analysis ofthe computed match scores according to a predetermined logic (e.g., ifnone of the computed match scores meet a predetermined threshold level).In yet another embodiment, the language analysis server transmits asolution page to the client based upon an analysis of the computed matchscores according to the predetermined logic (e.g., if at least one matchscore meets a predetermined high-threshold level).

In accordance with the invention, the method comprises transmitting aweb page having at least one user-interactable element for entering anatural language query and optional meta-data to a client, receiving thenatural language query and the optional meta-data, analyzing the naturallanguage query to classify the natural language query into at least onepredefined category using information contained within a knowledge base,and selectively transmitting a resource page to the client. The resourcepage includes at least one suggested response and optionally other datacorresponding to at least one predefined category.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an exemplary block diagram of a customer service network forprocessing an electronic query, according to one embodiment of theinvention;

FIG. 2 is an exemplary embodiment of the customer service interfaceillustrated in FIG. 1, according to one embodiment of the invention;

FIG. 3A illustrates an exemplary embodiment of a contact-us page,according to the invention;

FIG. 3B illustrates an exemplary embodiment of the drop-down boxcomponent illustrated in FIG. 3A, according to one embodiment of theinvention;

FIG. 3C illustrates an exemplary embodiment of the text field boxillustrated in FIG. 3A, according to one embodiment of the invention;

FIG. 4 illustrates one embodiment of the language analysis serverillustrated in FIG. 2, according to one embodiment of the invention;

FIG. 5 illustrates an exemplary communication-flow diagram forprocessing an electronic query as implemented by the customer servicenetwork illustrated in FIG. 1, according to one embodiment of theinvention; and

FIG. 6 illustrates exemplary method steps for processing an electronicquery, according to one embodiment of the invention.

DETAILED DESCRIPTION

FIG. 1 is an exemplary block diagram of a customer service network 100for processing an electronic query, according to one embodiment of thepresent invention. The customer service network 100 comprises a client105, a network 110 (e.g., the Internet), and a customer serviceinterface 115. The client 105 may comprise a browser 120 for browsingInternet web sites. According to one embodiment of the invention, thecustomer service interface 115 receives, classifies, and automaticallyresponds to electronic queries submitted by the client 105 via thenetwork 110. The customer service interface 115 is discussed furtherbelow in conjunction with FIG. 2.

FIG. 2 is an exemplary embodiment of the customer service interface 115illustrated in FIG. 1, according to one embodiment of the invention. Thecustomer service interface 115 comprises a server 205, a languageanalysis server 210, and a knowledge base 215. In an alternateembodiment, the language analysis server 210 and the knowledge base 215may be integrated in a single module. The server 205 preferablycomprises a web-server 220 for providing web services to the client 105(FIG. 1). For example, the web-server 220 may submit a contact-us pageto the client 105. The contact-us page allows a user to address anelectronic query to the customer service interface 115, and is discussedfurther below in conjunction with FIGS. 3A-3C. In addition, the server205 utilizes a script 225 for processing communications (i.e., queries)from the client 105. The script 205 may be any configurable ornon-configurable mechanism for routing information between variouscomponents of the customer service interface 115. The communicationsreceived by the server 205 contain data or information that isstructured and unstructured in nature. For example, the communicationstypically contain unstructured information expressed in naturallanguage. Each individual client correspondent may compose acommunication in a unique way, even when requesting the same type ofinformation from the customer service interface 115. In addition, thecommunications may contain structured information, such as meta-dataassociated with the communication, and queries in which the clientcorrespondent selects structured text displayed in drop-down menu boxes.Meta-data may additionally include, for example, information notexplicitly provided by the client correspondent, and informationregarding client correspondent attributes accessible to the customerservice interface 115. In one embodiment of the invention, the script225 parses the received communications, and sends the parsed informationto the language analysis server 210 for further analysis.

The language analysis server 210 analyzes and classifies the electronicquery comprising any combination of natural language text, structuredtext, and structured data (e.g., meta-data) into predefined categoriesstored in the knowledge base 215, based upon linguistic modeling rulesand concepts associated with the predefined categories. In oneembodiment, the language analysis server 210 linguistically analyzes thequery based upon content and context of the query, and classifies thequery to one or more of the predefined categories stored in theknowledge base 215 based upon a match score derived from a statisticalcomparison of concepts extracted from the query to concepts associatedwith the one or more predefined categories. In another embodiment, thelanguage analysis server 210 analyzes the query (i.e., extracts conceptsfrom the query) to match the query to the one or more predefinedcategories using standard search techniques. The language analysisserver 210 is discussed further below in conjunction with FIG. 4.

The knowledge base 215 is a branching network of nodes arranged in avertically structured hierarchy (i.e., tree hierarchy) that representthe various predefined categories. Logically related predefinedcategories are associated with a branch, which in turn may be associatedwith a branch of larger scope. Creation of the hierarchies can be eithermanual (via a configuration tool or an API), automatic by monitoringfeedback received via the client 105 or an agent, or a combination,whereby an automatic tool displays suggestions according to performanceof the customer service interface 115. A user may then create thehierarchies based upon the suggestions. The knowledge base 215 may alsoinclude flat hierarchies as a special case of tree hierarchies. Anembodiment of the language analysis server 210 and the knowledge base215 are discussed in more detail in patent application Ser. No. ______,entitled, “System and Method for Electronic Communication Management,”herein incorporated by reference, filed on an even date herewith.

FIG. 3A illustrates an exemplary embodiment of a contact-us page 310, ascomposed by the customer service interface 115 (FIG. 2) and transmittedto the client 105 (FIG. 1) via the network 110 (FIG. 1). The contact-uspage 310 may include a selectable text box 320 and a text field box 330for insertion of natural language text. In other embodiments, thecontact-us page 310 comprises multiple fields.

FIG. 3B illustrates an exemplary embodiment of the selectable text box320 illustrated in FIG. 3A, according to one embodiment of theinvention. The selectable text box 320 may include a plurality ofdrop-down boxes 322 that comprise predefined questions or statements,selectable by a user. For example, if the customer service interface 115 services a financial institution, then the drop-down boxes 322 mayinclude statements corresponding to customer service issues such asloans, new accounts, PIN numbers, monetary transfers, among others.

FIG. 3C illustrates an exemplary embodiment of the text field box 330illustrated in FIG. 3A, according to one embodiment of the invention.The text field box 330 comprises a selectable area in which the user maycompose a natural language message to the customer service interface115. For example, the user may not be able to access an electronicapplication for financial aid, partially completed and saved on a serverof the financial institution during a previous session. The user maycompose a message in the text field box 330, comprising, for example, “APIN number was sent to me when I electronically applied for financialaid. However, that PIN number does not allow me access to my financialaid account. Could you please rectify the situation?” As described inmore detail below in conjunction with FIGS. 5-6, the customer serviceinterface 115 classifies and responds to the message, either via a listof suggested responses, a direct link to a “solutions page,” or aconfirmation page to the client that the query is being routed to anagent for further analysis.

FIG. 4 illustrates one embodiment of the language analysis server 210 asillustrated in FIG. 2, according to one embodiment of the invention. Thelanguage analysis server 210 comprises a modeling application 410 and alanguage modeling engine 415. The modeling application serves as aninterface to the server 205 for receiving and transmittingcommunications. In addition, the modeling application 410 may comparematch scores (computed by the language modeling engine 415 inclassifying the query to predefined categories) with various predefinedthreshold scores to determine the nature of the automated response tothe client 105. The basis of the automated response to the client'squery is discussed below in further detail in association with FIGS.5-6.

The language modeling engine 415 analyzes and classifies naturallanguage text, structured text, and meta-data into predefined categoriesstored in the knowledge base 215. For example, the language modelingengine 415 analyzes the text and the meta-data by application oflinguistic and morphological models to extract concepts. The languagemodeling engine 415 then computes match scores based upon a comparisonof the extracted concepts with rules and concepts associated with thepredefined categories stored in the knowledge base 215. The computationof the match scores and further details of the knowledge base 215 arediscussed below in conjunction with FIGS. 5-6.

FIG. 5 is an exemplary communication-flow diagram for processing anelectronic query as implemented by the customer service network 100illustrated in FIG. 1, according to one embodiment of the invention.First, the web-server 220 (FIG. 2) serves a contact-us page 310 (FIG.3A) to the client 105 (FIG. 1) via a communication 510. The client 105responds to the contact-us page 310 via a communication 512. Forexample, the client 105 may respond to the contact-us page 310(hereinafter referred to as a client query, or simply a query) byselecting specific choices displayed in the drop-down boxes 322 (FIG.3B), by composing a natural language text in the text field box 330(FIG. 3C), or both. The web-server 220 receives the client query androutes the query to the script 225 (FIG. 2). The script 225 processesthe query, and routes the query to the language analysis server 210(FIG. 2) via a communication 514.

The language analysis server 210 linguistically and/or morphologicallyanalyzes the query based upon content and context of the query, andclassifies the query to one or more of the predefined categories storedin the knowledge base 215 (FIG. 2) via a communication 516. In oneembodiment of the invention, the language analysis server 210 classifiesthe query into the one or more predefined categories based upon a matchscore derived from a statistical comparison of concepts extracted fromthe query to concepts associated with the one or more predefinedcategories. The language analysis server 210 may utilize meta-data inaddition to conceptual data extracted from the query to classify thequery to the one or more predefined categories. For example, meta-dataincludes peripheral data not typically associated with content of thequery (i.e., with the natural language text and/or drop-down boxselections). For example, if the customer service interface 115 (FIG. 2)services a financial institution, then the peripheral data may includeuser name, user account number, or customer service plan afforded theuser. In accordance with a preferred embodiment of the invention, thelanguage analysis server 210 comprises classification techniques asdisclosed in patent application Ser. No. ______, entitled, “System andMethod for Electronic Communication Management,” herein incorporated byreference, filed on an even date herewith. However, the scope of thepresent invention covers standard classification techniques well knownin the art.

In one embodiment of the invention, the language analysis server 210computes, for each predefined category, a match score based uponconcepts associated with the predefined categories, concepts extractedfrom the query, and metadata. In an exemplary embodiment of theinvention, suppose that the customer service interface 115 services amotorcycle parts and equipment distribution house. Additionally, supposethat the knowledge base 215 has the following three predefinedcategories: a first predefined category entitled “new parts order,” asecond predefined category entitled “complaints,” and a third predefinedcategory entitled “suggestions.” A client correspondent submits to theserver 205 a query comprising a natural language text that states, forexample, “I am unhappy with the head gasket that you shipped me for my1955 BMW R50/2. The surface of the replacement gasket is cross-hatched(unlike the original), leading to reduced power and oil leakage. Pleaseeither refund my purchase, credit my account or send me the correctgasket.” In response to this query, the language analysis server 210computes a first, a second, and a third match score in classifying thequery to the first, the second, and the third predefined categories,respectively, where the second match score is greater than the firstmatch score, and the first match score is greater than the third matchscore. For example, the second match score may be 95, the first matchscore may be 42, and the third match score may be 16.

In one embodiment of the invention, each of the predefined categorieshas a corresponding resource, or linked suggested response in theknowledge base 215, and the relative values of the computed match scoresare indicative of a level of confidence of the corresponding suggestedresponses to answer the query or of the relevancy of the resource to thequery. For example, the second match score of 95 (relative to the firstand third match scores of 42 and 16, respectively) indicates that thequery is more likely to be resolved by the suggested response associatedwith the second predefined category than the suggested responsesassociated with the first or third predefined categories.

Next, the language analysis server 210 sends the suggested responses andcorresponding match scores to the server 205 via a communication 518. Inone embodiment of the invention, the customer service interface 115 isconfigured to respond to the communication 518 via either a first set ofcommunications (i.e., communications 520, 522, and 524) or a second setof communications initiated by a communication 526, depending upon thecorresponding match scores as described below.

If each of the corresponding match scores is less than a predeterminedthreshold score (where each predefined category may have a differentpredetermined threshold score), or based upon an analysis of the matchscores according to a predetermined logic, then the customer serviceinterface 115 responds via the first set of communications. Thepredetermined logic includes any functional analysis of the matchscores, exemplary embodiments of which include, but are not limited to,computations of an average match score, a median match score, a matchscore standard deviation, or other types of statistical and/or numericalfunctional analyses. In an exemplary embodiment of the first set ofcommunications, the server 205 sends a confirmation page to the client105 via a communication 520. The confirmation page informs the client105 that the query will be routed to an agent for further analysis. Thecommunication 520 may comprise additional information such as when theclient 105 may expect to receive a reply from the agent, for example. Inaddition, the language analysis server 210 routes the query to the agentfor further analysis via a communication 522. The agent may then replyto the client's query, preferably via an electronic message. However theagent may also respond to the query via alternate communicationchannels, such as a telephone, a Web-based reply, or other means ofelectronic communication. Optionally, the language analysis server 210may analyze the agent's reply, and, based upon the analysis, update theknowledge base 215 via a communication 524.

If, however, at least one of the corresponding match scores received bythe server 205 via the communication 518 is greater than or equal to thepredetermined threshold score (also referred to as a predeterminedthreshold level), then the customer service interface 115 responds withthe communication 526. In one embodiment of the invention, thecommunication 526 comprises a solution page. The communication 526comprises a solution page when at least one of the computed match scoreshas a very high value. Alternatively, the customer service interface 115may respond with the communication 526 that comprises the solution pagebased upon an analysis of the match scores according to thepredetermined logic as described above. For example, if the customerservice interface 115 services a financial institute, a clientcorrespondent may submit a query to the server 205 via the communication512 that recites, “I want to change my password.” If the customerservice interface 115 classifies the query to a “change password”predefined category with a high degree of certainty (e.g., the customerservice interface 115 classifies the query to the “change password”predefined category with a match score the meets a predeterminedhigh-threshold score), then the server 205 sends the client 105 a“password changing” web page (i.e., the solution page). In anotherembodiment, the server 205 re-directs the client 105 to the solutionpage corresponding to the “password changing” web page. The client 105may then utilize the solution page to resolve the query.

In another embodiment of the invention, the communication 526 maycomprise a resource page. For example, the server 205 sends the resourcepage to the client 105 comprising the suggested responses havingcorresponding match scores greater than or equal to the predeterminedthreshold level via the communication 526. The resource page may alsocomprise other data (such as links to web resources) havingcorresponding match scores greater than or equal to the predeterminedthreshold level. In one embodiment of the invention, the client 105 mayutilize one of several communicative actions (i.e., communicativeactions 528, 534, or 540) to respond to the resource page.

For example, the client 105 may select a suggested response on theresource page, respond to an embedded form on the resource page, orclick on a link to a web resource, via a first communicative action 528.The first communicative action 528 is received and processed by theserver 205, and the server 205 then routes the processed firstcommunicative action to the language analysis server 210 for linguisticanalysis via a communication 530. The language analysis server 210 mayoptionally update the knowledge base 215 via a communication 532 basedupon the linguistic analysis of the first communicative action 528.

Alternatively, the client 105 may respond to the resource page via asecond communicative action 534. The second communicative action 534comprises a non-response to the resource page. More specifically, theclient 105 does not respond to the resource page (i.e., the client isnon-responsive). For example, in one embodiment of the invention, if theclient 105 does not respond to the resource page within a given timelimit, or if the client 105 disconnects from the server 205, forexample, the second communicative action 534 comprising a non-responseis sent to the server 205. The server 205 then sends a communication 536to the language analysis server 210 indicating the non-response. Thelanguage analysis server 210 may update the knowledge base 215 basedupon the non-responsiveness of the client 105 via an optionalcommunication 538.

As an additional alternative, the client 105 may respond to the resourcepage via a third communicative action 540 comprising a communicativeescalation. For example, the client 105 may select (e.g., bymouse-clicking) a “request for help” button embedded in the resourcepage, or request more information regarding a particular suggestedresponse. The server 205 receives the third communicative action 540comprising the communicative escalation, and routes the communicativeescalation to the language analysis server 210 via a communication 542.The language analysis server 210 then sends the communicative escalationto the agent for further analysis via a communication 544. The languageanalysis server 210 may optionally update the knowledge base 215 basedupon the agent's reply to the communicative escalation via acommunication 546.

FIG. 6 illustrates exemplary method steps for processing an electronicquery, according to one embodiment of the invention. In step 610, theclient 105 (FIG. 1) submits an electronic query to a web-site. In oneembodiment, the query may be in response to a page served to the client105 by the web-server 220 (FIG. 2) associated with the web site. Theclient 105 may be running the browser 120 (FIG. 1) to view the pageserved by the web-server 220. Next, in step 615, the server 205 (FIG. 2)intercepts and routes the query. For example, the server 205 may run thescript 225 (FIG. 2) that processes the query and routes the processedquery to the language analysis server 210 (FIG. 2).

In step 620, the language analysis server 210 analyzes the query usingthe language modeling engine 415 (FIG. 4) and the knowledge base 215(FIG. 2) to compute match scores and classify the query to predefinedcategories stored in the knowledge base 215 based upon the match scores,where each predefined category is associated with a suggested response.In one embodiment of the invention, the knowledge base 215 is configuredas a rule-oriented/concept-oriented database. For example, the knowledgebase 215 may comprise a plurality of nodes configured in ahierarchically structured branching network, where each node isconfigured as either a rule-oriented or a concept-oriented node. Eachconcept-oriented node is typically associated with a predefinedcategory. In one embodiment of the invention, the language analysisserver 210 utilizes a statistical process to compute the match scores.For example, the language modeling engine 415 analyzes the naturallanguage text of the query to generate concepts associated with thequery. The language modeling engine 415 then statistically compares thequery-derived concepts with rules associated with the rule-orientednodes and with concepts associated with the concept-oriented nodesstored in the knowledge base 215. The language modeling engine 415 thencomputes a match score for one or more concept-oriented nodes (i.e., forone or more predefined categories). In one embodiment, a high matchscore for a particular predefined category indicates that a suggestedresponse corresponding to the predefined category is more likely to be acorrect response than a suggested response corresponding to a predefinedcategory with a low match score. Based upon the computed match scores,the modeling application 410 (FIG. 4) determines if the query meets anyof the predetermined threshold levels for an automated response.

For example, if each match score associated with each predefinedcategory is less than a corresponding predetermined threshold level,then in step 625, the modeling application 410 routes the query to anagent for further analysis. Preferably, the agent is a human agent.However, in alternate embodiments, the agent may be an automatedservice, such as an automated phone service or an automated computersystem. Next, in step 630, the server 205 sends the client 105 aconfirmation page. In one embodiment, the confirmation page comprises acommunication confirming that the client's query is being routed to theagent for further analysis. Next, in step 635, the agent replies to thequery. In one embodiment of the invention, the agent replies to theclient 105 via an electronic mail system. However, the scope of thepresent invention covers alternate agent-reply methods, such asweb-based, telephonic, or facsimile methods.

Next, in optional step 640, the language analysis server 210 processesthe agent's reply to the client to generate agent-based feedback. Thelanguage analysis server 210 may then update the knowledge base 215based upon the agent-based feedback. The agent-based feedback maycomprise positive or negative feedback. The language analysis server 210uses the feedback to modify the knowledge base. For example, thelanguage analysis server 210 may modify concepts, add new concepts,eliminate concepts, or modify weights assigned to different conceptsassociated with concept-oriented nodes. The language analysis server 210may also modify relationships between nodes, such as structuralrelationships defined by branching structures, for example. In alternateembodiments, the language analysis server 210 may modify classificationrules associated with rule-oriented nodes stored in the knowledge base215.

Referring back to step 620, if at least one match score associated withat least one predefined category is greater than or equal to acorresponding predetermined threshold level, then in step 645, theserver 205 submits a resource page to the client 105. The resource pagemay comprise a suggested response page, where each suggested responsecorresponds to a predefined category with an associated match scoregreater than or equal to the corresponding threshold level. A suggestedresponse may include a message that recites, for example, “no responsewas found.” Alternatively, if an associated match score is greater thanor equal to a corresponding high-threshold level, then the resource pagecomprises a solution page that provides either a link or a web page tothe client 105 that may directly resolve the query. Each predefinedcategory may have different threshold levels and high-threshold levels.Next, in step 650, the client 105 responds to the resource page and theserver 205 determines whether the client query is resolved based uponthe client response. In one embodiment of the invention, the query isnot resolved if the client 105 escalates (e.g., the client 105 respondswith a request for help), and the process then continues at step 625.

However, if in step 650 the query is resolved, then in optional step655, the language analysis server 210 receives client-based feedback(i.e., feedback based upon the client's response). In one embodiment ofthe invention, the query is considered resolved if the client 105selects a suggested response, or if the client 105 does not select anyresponse (i.e., the client 105 is non-responsive).

In optional step 655, the language analysis server 210 updates. theknowledge base 215 based upon the client-based feedback. For example, aselection of a suggested response corresponding to a high match scoregenerates a positive client-based feedback that may strengthen theconcept-oriented nodes of the knowledge base 215 that generated thesuggested responses. In one embodiment of the invention, aconcept-oriented node may be strengthened by redistributing weightsassigned to concepts associated with the node. However, if the client105 selects a suggested response corresponding to a low match score,then the client 105 generates negative client-based feedback that maymodify the concept-oriented nodes and branching structures thatgenerated the selected suggested response.

The present invention has been described above with reference toexemplary embodiments. Other embodiments will be apparent to thoseskilled in the art in light of this disclosure. The present inventionmay readily be implemented using configurations other than thosedescribed in the exemplary embodiments above. Therefore, these and othervariations upon the exemplary embodiments are covered by the presentinvention.

1-10. (canceled)
 11. A method for processing a web-based query,comprising: transmitting a web page to a client for display, the webpage including at least one user-interactable element for entering anatural language query and the web form including meta-data that is notassociated with the natural language query's content; receiving thenatural language query and the meta-data from the client; analyzing thenatural language query and the meta-data to classify the naturallanguage query into at least one predefined category using informationcontained within a knowledge base; and selectively transmitting aresource page to the client for display, the resource page including atleast one suggested response and optionally other data corresponding tothe at least one predefined category.
 12. The method of claim 11,further comprising: receiving a communicative action from the client;and adapting the knowledge base in accordance with the communicativeaction.
 13. The method of claim 11, further comprising: calculating aset of match scores, each match score of the set of match scorescorresponding to one of a plurality of predefined categories and beingrepresentative of a confidence level that the natural language query isrelevant to the one of the plurality of predefined categories; andclassifying the natural language query into the at least one predefinedcategory based on a match score associated therewith.
 14. The method ofclaim 13, further comprising routing the natural language query to anagent if none of the match scores of the set of match scores meet apredetermined threshold level.
 15. The method of claim 13, furthercomprising routing the natural language query to an agent based upon ananalysis of the set of match scores according to a predetermined logic.16. The method of claim 15, further comprising transmitting to theclient a confirmation page confirming that the natural language queryhas been routed to the agent.
 17. The method of claim 15, furthercomprising updating the knowledge base according to the agent's responseto the natural language query.
 18. The method of claim 13, furthercomprising transmitting a solution page to the client if at least onematch score of the set of match scores meet a predeterminedhigh-threshold level.
 19. The method of claim 13, further comprisingtransmitting a solution page to the client based upon an analysis of theset of match scores according to a predetermined logic.
 20. The methodof claim 11, wherein the other data comprises one or more links to webresources.
 21. A computer-readable storage medium having embodiedthereon a program, the program being executable by a computer to performa method for processing a web-based query, the method comprising:transmitting a web page to a client for display, the web page includingat least one user-interactable element for entering a natural languagequery and the web form including meta-data that is not associated withthe natural language query's content; receiving the natural languagequery and the meta-data from the client; analyzing the natural languagequery and the meta-data to classify the natural language query into atleast one predefined category using information contained within aknowledge base; and selectively transmitting a resource page to theclient for display, the resource page including at least one suggestedresponse and optionally other data corresponding to the at least onepredefined category.
 22. A method for processing a web-based query,comprising: means for transmitting a web page to a client for display,the web page including at least one user-interactable element forentering a natural language query and the web form including meta-datathat is not associated with the natural language query's content; meansfor receiving the natural language query and the meta-data from theclient; means for analyzing the natural language query and the meta-datato classify the natural language query into at least one predefinedcategory using information contained within a knowledge base; and meansfor selectively transmitting a resource page to the client for display,the resource page including at least one suggested response andoptionally other data corresponding to the at least one predefinedcategory.